The Role of Asphaltenes in Emulsion Formation for Steam Assisted Gravity Drainage (SAGD) and Expanding Solvent - SAGD (ES-SAGD)
Bibliographic record
Abstract
Abstract Steam Assisted Gravity Drainage (SAGD) and Expanding Solvent SAGD (ES-SAGD) have previously been compared and ES-SAGD has shown improved oil recovery with lower energy and water requirements and significant oil upgrading. However, solvent selection is the key factor which determines the performance of ES-SAGD due to the asphaltene-solvent interaction. The change in asphaltene stability with the solvent type can have several drawbacks during ES-SAGD. Stable emulsion formation is one of these problems which have not been investigated thoroughly for ES-SAGD. In this study, we characterized both water-in-oil and oil-in-water type of emulsions originating from SAGD, SAGD with n-hexane and SAGD with n-hexane and toluene mixture experiments. These three experiments were conducted on 8.65 °API Canadian bitumen with 34.3 wt% asphaltene content. Structural changes in produced oil, produced water, and spent rock samples were analyzed with Fourier Transform Infrared (FTIR) spectroscopy. Emulsions in produced oil and water samples were determined with microscopic images. The differences in emulsions were interpreted with the wettability change determined on spent rock samples. Moreover, the asphaltene fraction of produced oil samples is further analyzed with FTIR and zeta potential measurements. For produced oil, the greatest asphaltene content with more severe emulsion formations were detected on the sample originating from SAGD. In terms of stability, because the asphaltenes originating from both ES-SAGD experiments have higher zeta potential values, lower emulsion stability has been observed for the produced oil originating from ES-SAGD. In summary, the role of asphaltenes on emulsion formation has been studied for SAGD and ES-SAGD for bitumen extraction. ES-SAGD with asphaltene soluble solvents leads to the formation of less stable emulsions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".